From: raphael couturier Date: Wed, 13 Aug 2014 17:35:33 +0000 (+0200) Subject: modif de LSQR qui fonctionne quand meme mieux (un poil moins rapide que CGLS quand... X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/GMRES2stage.git/commitdiff_plain/90a7d5a4672d8b4883fce5722939a29439b059d2 modif de LSQR qui fonctionne quand meme mieux (un poil moins rapide que CGLS quand meme) --- diff --git a/code/ex15.c b/code/ex15.c index 0e0a8c4..94c9365 100644 --- a/code/ex15.c +++ b/code/ex15.c @@ -1,5 +1,5 @@ -// /home/couturie/work/petsc-3.5.1/arch-linux2-c-debug/bin/mpirun -np 4 ./ex15 -m 400 -n 400 +// /home/couturie/work/petsc-3.5.1/arch-linux2-c-debug/bin/mpirun -np 4 ./ex15 -m 400 -n 400 -ksp_type fgmres @@ -232,7 +232,7 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { PetscScalar alpha, beta; PetscReal norm=20, Eprecision=1e-8, tol=1e-40; - PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0; + PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=20, Iiter=0; PetscErrorCode ierr; PetscScalar T1, T2; KSP ksp; @@ -419,14 +419,14 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { VecAYPX(d,-thet,v); //d = (v - thet * d); VecAYPX(d,1/rho,zero_short); //d=d/ rho; - + /* if (normar/(norma*normr) <= tol) { // check for convergence in min{|b-A*x|} break; } if (normr <= tolb) { // check for convergence in A*x=b break; } - + */ VecAXPY(x_lsqr,phi,d); // x_lsqr=x_lsqr+phi*d normr = abs(s) * normr; @@ -630,7 +630,7 @@ int main(int argc,char **args) VecDuplicate(b,&x2); VecDuplicate(b,&sol); - KrylovMinimize(A, b, x2); + KrylovMinimizeLSQR(A, b, x2); diff --git a/code/ex29.c b/code/ex29.c index 5e21c65..ede2355 100644 --- a/code/ex29.c +++ b/code/ex29.c @@ -1,6 +1,6 @@ -// /home/couturie/work/petsc-3.5.1/arch-linux2-c-debug/bin/mpirun -np 3 ex29 -da_grid_x 900 -da_grid_y 900 +// /home/couturie/work/petsc-3.5.1/arch-linux2-c-debug/bin/mpirun -np 3 ex29 -da_grid_x 900 -da_grid_y 900 -ksp_type fgmres @@ -240,7 +240,7 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { PetscScalar alpha, beta; PetscReal norm=20, Eprecision=1e-5, tol=1e-40; - PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0; + PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=20, Iiter=0; PetscErrorCode ierr; PetscScalar T1, T2; KSP ksp; @@ -428,13 +428,6 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { VecAYPX(d,1/rho,zero_short); //d=d/ rho; - if (normar/(norma*normr) <= tol) { // check for convergence in min{|b-A*x|} - break; - } - if (normr <= tolb) { // check for convergence in A*x=b - break; - } - VecAXPY(x_lsqr,phi,d); // x_lsqr=x_lsqr+phi*d normr = abs(s) * normr; diff --git a/code/ex45.c b/code/ex45.c index a44a2d0..11fd5c2 100644 --- a/code/ex45.c +++ b/code/ex45.c @@ -408,14 +408,6 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { VecAYPX(d,1/rho,zero_short); //d=d/ rho; - if (normar/(norma*normr) <= tol) { // check for convergence in min{|b-A*x|} - break; - } - if (normr <= tolb) { // check for convergence in A*x=b - break; - } - - VecAXPY(x_lsqr,phi,d); // x_lsqr=x_lsqr+phi*d normr = abs(s) * normr; MatMultTranspose(AS, u, vt); //vt=A'*u;